What You’ll Find in this Case Study:
- About the client
- Area of Engagement
- Predictive Sentiment Analysis Challenge Faced by the Client
- Solutions’ Benefits and Business Impact
- Sentiment Analysis Predictive Insights
The client: Food service client
Area of engagement: Predictive Sentiment analysis
Food service industry is slowly evolving into a global industry with operators and manufacturers contributing a majority of the market share globally. The food service at large comprises of all companies engaged in serving meals for immediate consumption such as restaurants, cafeterias, and catering outlets. Innovations, customization in the food products, and the rising demand for nutritious food among the target audiences are effectively contributing to the growth of the food service space. Although the food service market is witnessing a promising growth, owing to the presence of a considerable number of leading-edge players, several factors may influence the growth of the market. They include:
Compliance issues: With the growing concern for health and wellness, it becomes a mandate for the organizations to ensure better quality in the products offered. The public health service departments across the globe are forcing organizations to ensure that the quality of the food products offered is on par with the recommended standards.
Lack of labor power: Since the food service industry contributes to a majority of the market share globally, the labor force is not on par with the growing food service outlets. Moreover, leading organizations are facing the need to include employee retention strategies as a part of their operations to hire employees and retain the most profitable ones.
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Innovations: The global food service space is witnessing a relentless competition to deliver more personalized offerings to the customers. With the growing threat of new entrants, organizations are facing the need to invest heavily in R&D and offer innovations in terms of packaging for home delivery or take away foods.
To address these challenges and address the growing demand of the target audiences, organizations in the food and beverage industry are utilizing the need for a sentiment analytics solution. A sentiment analytics solution helps businesses understand the thoughts and opinions of the customers and analyze their social media campaigns to identify opinions of the customer segments.
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Predictive Sentiment Analysis Business Challenge
According to a recent study, the food service space accounts for approximately 10% of the total workforce globally.
The client, a renowned food service provider, wanted to uncover and translate social data into tangible insights and gain valuable information into the trending conversations, threads, and posts. With the help of a sentiment analysis solution, the client wanted to monitor the sentiment around your brand and products accurately. The primary concern of the food service client was to profile the competitors and assess the perceptions of the customers around their activities. The sentiment analysis solution also aimed at identifying potential influencers across several channels.
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The Solution Benefits and the Business Impact
The predictive sentiment analysis solution offered by Quantzig helped the food service client assess the perceptions of the customers toward the brand. The client also sought ways to determine the sentiment of the customers through scoring algorithms. Moreover, the food service client was able to extract information from available sources such as online reviews and social media discussions to further optimize the company’s products and services. The engagement also determined the feedbacks from the customers’ and helped the client conduct social market research.
Sentiment Analysis Predictive Insights
Quantzig’s predictive sentiment analysis solution helped the food service client extract sentiment in real-time over a considerable period using statistical modeling techniques. The solution also helped the client actively combine the information from social networking sites and identify feedback sources to define new targets. The sentiment analysis solution further helped the food service client evaluate the internal and external content and classify the content based on positive, negative, neutral, and no sentiment texts.
